---
library_name: transformers
language:
- ro
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Tiny Ro (local) - Augustin Jianu
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 17.0
      type: mozilla-foundation/common_voice_17_0
      config: ro
      split: test
      args: 'config: ro, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 37.48352861569144
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# Whisper Tiny Ro (local) - Augustin Jianu

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 17.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5978
- Wer: 37.4835

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Wer     |
|:-------------:|:-------:|:-----:|:---------------:|:-------:|
| 0.4417        | 1.7730  | 1000  | 0.5327          | 43.8513 |
| 0.1813        | 3.5461  | 2000  | 0.4666          | 38.8689 |
| 0.0751        | 5.3191  | 3000  | 0.4645          | 36.5006 |
| 0.0326        | 7.0922  | 4000  | 0.4803          | 36.4614 |
| 0.0234        | 8.8652  | 5000  | 0.5087          | 36.5148 |
| 0.0082        | 10.6383 | 6000  | 0.5424          | 36.6252 |
| 0.0042        | 12.4113 | 7000  | 0.5650          | 37.6509 |
| 0.0029        | 14.1844 | 8000  | 0.5809          | 36.8710 |
| 0.0025        | 15.9574 | 9000  | 0.5922          | 38.1495 |
| 0.0021        | 17.7305 | 10000 | 0.5978          | 37.4835 |


### Framework versions

- Transformers 4.48.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0